The “background” description provided herein is for the purpose of generally presenting the context of the disclosure. Work of the presently named inventors, to the extent it is described in this background section, as well as aspects of the description which may not otherwise qualify as prior art at the time of filing, are neither expressly or impliedly admitted as prior art against the present invention.
Node clustering is a beneficial technique for applications that require a high scalability of tens to hundreds of sensor nodes. This may be due to heavier loads placed upon sensor nodes near a monitoring unit.
Typically, a long-distance pipeline distribution system is used to transport water from a water reservoir to a metropolis. For example, in Saudi Arabia, long pipelines are used to transfer water from the Shoaiba Desalination Plant in Al-Jubail, a city in eastern province of Saudi Arabia, to Riyadh. See I. Jawhar and N. Mohamed, “A hierarchical and topological classification of linear sensor networks,” 2009 Wirel. Telecommun. Symp. WTS 2009, 2009.
Online pipeline monitoring helps maintain proper operation and also has environmental and safety advantages. Long distance pipelines and pipelines carrying critical supplies need to be continuously monitored to avoid any potential damage. However, the expected topology for pipeline placement may be linear which poses many challenges in placing sensors optimally.
In recent years, attention has been devoted on node placement in linear topology (i.e. pipeline monitoring systems). In Xue, the authors disclosed an algorithm that supports the proper selection for the relay sensor node placement and accordingly selects the transmission power levels of sensor nodes that provides the maximum lifetime. See G. Xue, “Relay node placement in wireless sensor networks for pipeline inspection,” Am. Control Conf., vol. 13, no. 7, pp. 5905-5910, 2013. However, these studies have not taken into consideration sudden damage scenarios. The monitoring in this case is only temporary.
Similarly, Guo et al. have studied equal-power and equal-distance node placement schemes. Two heuristics were disclosed for sensor node placement with a view towards improving the lifetime of the network by proposing an evenly consumed power model, which increases the number of sensor nodes closer to the base station and configures these sensor nodes to carry the data at lower power. See Y. Guo, F. Kong, D. Zhu, A. S. Tosun, and Q. Deng, “Sensor Placement for Lifetime Maximization in Monitoring Oil Pipelines,” Proc. 1st ACM/IEEE Int. Conf Cyber-Physical Syst.—ICCPS '10, pp. 61-68, 2010.
Djame et al. took advantage of energy harvesting capabilities. See D. Djenouri and M. Bagaa, “Energy harvesting aware relay node addition for power-efficient coverage in wireless sensor networks,” in IEEE International Conference on Communications, 2015, vol. 2015-Septe, pp. 86-91. Generally, it was proposed to use harvesting-enabled sensor nodes for only relaying the packets and non-harvesting sensor nodes for sensing and transmitting their readings to relay sensor nodes.
In relation to node placement on pipeline monitoring, a non-uniform scheme called linearly decreasing distance (LDD) has been presented by Alnuem. See M. Alnuem, “Performance Analysis of Node Placement in Linear Wireless Sensor Networks,” vol. 5, no. 1, pp. 1-8, 2014. LDD gradually reduces the distance among sensor nodes, wherein the sensor nodes are placed near the gateway.
In Cheng et al., a constrained multivariable nonlinear programming problem has been formulated. See P. Cheng and C. Chuah, “Energy-aware Node Placement in Wireless Sensor Networks,” pp. 3210-3214, 2004. The results show that the performance of the optimal node placement strategies is better than uniform node placement strategies.
Alduraibi et al have studied the coverage problem when the event detectability varies with proximity to the sensor node and when some desired level of sensing fidelity is to be maintained. See F. Alduraibi, N. Lasla, and M. Younis, “Coverage-based Node Placement Optimization in Wireless Sensor Network with Linear Topology,” 2016. Three optimization models have been presented to determine the node density.
Node placement in WSNs has been widely investigated. However, only a few studies have been devoted to pipeline applications where the sensor nodes are deployed linearly. Moreover, few of these studies have adopted a realistic power model without considering all-discrete power levels. In addition, most of the studies use greedy heuristic approaches which increase the density of sensor nodes with lower power levels nearest to the base station (BS). Also, all sensor nodes are responsible for forwarding the data packets towards the BS all the time. Moreover, these solutions do not introduce the reliable communication in a practical manner because the access can only be one way. In addition, most of the previous studies did not consider the required fidelity of the sensor nodes.